Image Enhancement and Restoration: Deep Learning for Image Dehazing

Image dehazing is a critical task in computer vision that involves removing the haze or fog from an image to enhance visibility and improve quality. Methods based on deep learning for image dehazing have demonstrated promising results in recent years, utilising the ability of neural networks for learning how to map of a blurry picture to a clear one. This study presents a thorough analysis of current deep learning methods for image dehazing. We analyze and compare these methods based on their underlying principles, strengths, and limitations. We categorize them into different approaches and evaluate their performance using standard metrics. Moreover, this paper will also explore the challenges and future directions in advancements of deep learning-based image dehazing.